WWCD优化Canopy-K-means的雷达信号分选算法  

Radar Signal Sorting Algorithm of WWCD Optimization Canopy-K-Means

作　　者：王之腾 李尚远 纪存孝 刘畅 严子路 WANG Zhiteng;LI Shangyuan;JI Cunxiao;LIU Chang;YAN Zilu(College of Communications Engineering,Army Engineering University of PLA,Nanjing 210007,China)

机构地区：[1]陆军工程大学通信工程学院,江苏南京210007

出　　处：《陆军工程大学学报》2025年第1期20-26,共7页Journal of Army Engineering University of PLA

基　　金：国家自然科学基金青年项目(62301604)。

摘　　要：雷达信号分选是电子战系统中的关键技术,是战场态势感知的重要环节,新体制雷达技术的快速发展给复杂电磁环境下信号分选带来了严峻挑战。针对传统K-means聚类算法在对雷达全脉冲数据进行信号分选时存在对聚类数K和初始点选择较为敏感的问题,提出了一种基于优化K-means的雷达信号分选算法。通过将水波中心扩散(water wave center diffusion,WWCD)优化算法和Canopy算法相结合,实现了Canopy算法距离阈值的优选,并为后续K-means聚类优化了K值的选择,有效降低了K-means算法对初始聚类数选择的敏感性。实验中,主要通过3个UCI公开数据集和3类频率跳变雷达脉冲数据进行聚类分选效果验证,并与常见的DBSCAN、OPTICS、Canopy-K-means等聚类算法进行了聚类效果对比。结果表明,所提方法有较高的聚类分选准确率,且对初始参数的设置不敏感。Radar signal sorting is a key technology in the electronic warfare system and an essential part of battlefield situational awareness.The development of new system radar technology brings a serious challenge to radar signal sorting in the current complex battlefield electromagnetic environment.For the problem that the traditional K-means clustering algorithm is sensitive to the initial cluster number K and the initial points when performing signal sorting on radar full pulse data,an optimized K-means-based radar signal sorting algorithm is proposed.The combination of water wave center diffusion(WWCD)optimization algorithm and the Canopy algorithm realizes the optimal selection of the distance threshold of the Canopy algorithm,and optimizes the selection of the cluster number K for K-means clustering,effectively reducing the sensitivity of the K-means algorithm to the selection of the initial number of clusters.Three kinds of UCI data and three kinds of frequency-hopping radar pulse data are used to verify the sorting performance of the proposed method,and the clustering effects are also compared with common clustering algorithms such as DBSCAN,OPTICS,and Canopy-K-means.The results show that the proposed method is insensitive to the setting of initial parameters and has a high clustering and sorting accuracy.

关 键 词：雷达信号分选 水波中心扩散优化 Canopy算法 K-MEANS算法 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]